DIGDATA CHALLENGE
ON ENERGY
APPLICATION CLOSED ON
MARCH 15, 2021

TYPES OF DATA 

 

Energy Efficiency:

With energy efficiency data, participants may analyze and compare the introduction and sustained use of energy efficiency measures, their potential savings, and investment costs with baseline consumption. Coupled with the data on costs (MAR), household consumption and other relevant data, this data can be used to analyze potential energy savings from energy efficiency investments. Since many energy efficiency investments are both low-cost and incremental, an analysis of this data can help customers understand the marginal benefits of reducing the use of costly appliances or investing in energy efficiency measures (more efficient appliances, sealing windows, insulating walls).  For example, by changing to more energy efficient compact fluorescent bulbs, a customer can save an average of two-thirds the amount of electricity compared to traditional incandescent light bulbs.  The data on investment in energy efficiency measures and the inventory of publicly owned buildings can also be used to analyze the costs, savings, prevalence, and adherence of existing commercial programs for energy efficiency.

 

Maximum Allowed Revenues (MAR)

Maximum Allowed Revenues data from the Universal Service Supply, the Distribution System Operator, and Transmission System Operator allows participants to analyze the Kosovo energy sector’s costs relative to tariffs. The data also contains energy import and export prices. Using this data, participants may analyze consumers’ bills to analyze and interpret the percentage of the electricity bill that is dedicated to generation costs (divided into costs for lignite and renewable sources, and imports), transmission costs, distribution costs (including identifying also the costs that are associated with losses in the network), and supply costs.  This data could potentially be used for solutions that communicate trends in billing and analyze whether revenue collection is keeping pace with the Government of Kosovo’s commitments to capital investments in energy generation, renewable energy, and energy efficiency.

 

Consumption data:

Participants may use consumption data to analyze differences in how various consumer groups use energy, and their associated electricity losses (divided into technical, commercial and unbilled supply). This data contains information on household, commercial and industrial consumption, including transmission, distribution losses, unbilled supply, and energy used for mines and generating units at KEK. Consumption data also includes the average tariffs for households, commercial and industrial customers. The data also contains billing determinants for households.  Finally, it includes energy consumption patterns over the course of the day and night time so that participants might analyze the effects of energy consumption at different times of day. Competitors may wish to compare this data with air quality data to propose solutions that incentivize customers to reduce energy consumption during peak demand or poor air quality conditions.  These data could also be used to analyze Kosovo’s consumption patterns and prices relative to consumption and prices in other countries and propose proven or promising policy or/and personal solutions to improve public trust, revenue collection, accountability, efficiency and/or consumption patterns.

 

Household consumption data:

Household consumption data allows for in-depth analysis of the household average consumption and household price (tariff) structures. Competitors may use data on household consumption in different districts and consumption in rural versus urban areas to analyze differences between various households based on location. When paired with information available from local sources or international data sources on appliance power consumption, competitors could propose solutions on appliances, programming, policies, or incentives that could reduce household and local energy consumption or improve efficiency. These data could be used to analyze the difference of average consumption difference between districts (cities), as well as differences in average consumption of urban vs rural areas. Together with data on household appliance power consumption, the data can be used to analyze how using certain appliances affects the total monthly consumption, and how changing behaviors might affect the consumer’s bills. The competitors will also have access to consumption data for vulnerable socioeconomic households receiving subsidies from the Ministry of Labor and Social Welfare, such as households qualifying for social assistance or veteran’s pensions. When paired with other available data, the competitors may develop solutions that empower vulnerable groups to understand their electricity, consumption, know their rights and lower their electricity bills.   

 

Consumer complaint data:

Consumer complaint data contains data on: 1. Customer complaints to the supplier by month, 2. Customer complaints to the supplier by District, 3. Customer complaints to the supplier by Nature, 4. Customer complaints to ERO against supplier by customer categories (nature), 5. Customer complaints to ERO against suppliers by the nature of complaints 6. Customer complaints by customers against ERO’s decision in the court, 7. Supplier complaints against ERO’s decision to the court concerning customer complaints. This data category also includes complaint outcomes as to whether complaints are refused versus decided in favor of customers. These data could be used to analyze patterns of customer complaints, rulings on complaints, and complaints in various districts.  This data could be used to formulate solutions that could shine a light on and inspire collective action around persistent service or revenue collection failures, disparities in customer treatment, or unjust rulings.  Alternatively, it could be used to formulate solutions which address customer misperceptions around service provision and rate-setting.

 

Network loss data:

Competitors may use network loss data to analyze energy losses and their locations. The data contains information on monthly losses divided into districts for both technical and commercial losses. Together with other sets of data, such as data on costs (MAR), data on consumption, and in particular data on household consumption, these data could be used to analyze in detail the impact of costs for losses in customers electricity bills.

Network losses of electricity in Kosovo remain high, approximately 26% of total consumption in distribution is accounted for as losses in the network. While technical losses, mainly coming as a result of old network infrastructure and planning, account for 13% of total consumption, the rest are commercial losses or unauthorized use of electricity. Only through tariffs the costs of losses are envisaged to amount to approximately 46.88 million Euro for the period 1 April 2020 – 31 March 2021, considering entire costs of Distribution 95.40 Euro millions, is 49% of total costs of distribution.

 

Generation data:

Competitors may use generation data to analyze electricity generation by each individual generator and the average prices of different electricity sources (e.g., for KEK generation, for renewable sources generation).  These data are also reflected in the costs noted in MAR data. This data category also contains data on electricity imports and exports. The data includes the expected generation of electricity (RES targets) from renewable sources to meet the renewable goals and the feed-in tariff prices. The available data includes renewable projects that have been authorized by ERO to develop new generation capacities and which will be supported by existing tariffs paid to renewable energy generators (“feed in tariffs”) set by ERO. The data includes the projected generation (in MWh) after construction is complete, and the applicable feed in tariffs. The data could be used to analyze what is being generated relative to costs (both financial and environmental), as well as what may be the costs of generation in the future if renewable generation goals are met. The data could also be used to analyze the impacts of market liberalization in the cost to customers and the price of various European power exchanges.

 

Environmental pollution data

Competitors may use environmental pollution data to analyze the effects of using lignite coal for electricity generation. The data contains information on lignite production and consumption, as well as data for pollutants from mining and electricity generation. These data could be used to analyze electricity generation pollution from KEK (lignite sources).  When coupled with information from the energy generation data set, competitors would be able to analyze and propose solutions vis-a-vis addressing the impacts of renewable energy sources on pollution.  This data could also be paired with air quality data and or consumption data to propose solutions for improved citizen health.

For more detailed information on the data, please refer to the Data Guide.

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